Update training_bert.py

training_bert.py

@@ -1,7 +1,12 @@
 import pandas as pd
 import numpy as np
 import re
+from transformers import Trainer
+import torch
 from sklearn.model_selection import GroupShuffleSplit
+from transformers import AutoTokenizer,AutoModelForSequenceClassification
+from transformers import TrainingArguments
+
 def remove_links(review):
     pattern = r'\bhttps?://\S+'
     return re.sub(pattern, '', review)
@@ -34,7 +39,7 @@ y_val = val.Score
 X_test = test.drop(columns = 'Score')
 y_test = test.Score
 
-from transformers import AutoTokenizer,AutoModelForSequenceClassification
+
 base_model = 'bert-base-cased'
 learning_rate = 2e-5
 max_length = 64
@@ -78,7 +83,7 @@ def compute_metrics_for_regression(eval_pred):
 
     return {"mse": mse, "mae": mae, "r2": r2, "accuracy": accuracy}
 
-from transformers import TrainingArguments
+
 
 output_dir = ".."
 
@@ -94,8 +99,7 @@ training_args = TrainingArguments(
     load_best_model_at_end=True,
     weight_decay=0.01,
 )
-from transformers import Trainer
-import torch
+
 class RegressionTrainer(Trainer):
     def compute_loss(self, model, inputs, return_outputs=False):
         labels = inputs.pop("labels")